New methods in genetics research, such as linkage disequilibrium score regression (LDSR), quantify overlap in the common genetic variants that influence diverse phenotypes. It is becoming clear that genetic effects often cut across traditional diagnostic boundaries. Here, we introduce genetic correlation analysis (using LDSR) to a nongeneticist audience and report transdisciplinary discoveries about schizophrenia. This analytical study design used publically available genome wide association study (GWAS) data from approximately 1.5 million individuals. Genetic correlations between schizophrenia and 172 medical, psychiatric, personality, and metabolomic phenotypes were calculated using LDSR, as implemented in LDHub in order to identify known and new genetic correlations. Consistent with previous research, the strongest genetic correlation was with bipolar disorder. Positive genetic correlations were also found between schizophrenia and all other psychiatric phenotypes tested, the personality traits of neuroticism and openness to experience, and cigarette smoking. Novel results were found with medical phenotypes: schizophrenia was negatively genetically correlated with serum citrate, positively correlated with inflammatory bowel disease, and negatively correlated with BMI, hip, and waist circumference. The serum citrate finding provides a potential link between rare cases of schizophrenia (strongly influenced by 22q11.2 deletions) and more typical cases of schizophrenia (with polygenic influences). Overall, these genetic correlation findings match epidemiological findings, suggesting that common variant genetic effects are part of the scaffolding underlying phenotypic comorbidity. The "genetic correlation profile" is a succinct report of shared genetic effects, is easily updated with new information (eg, from future GWAS), and should become part of basic disease knowledge about schizophrenia.